ParalonCloud Rentals — MCP server

Rent GPUs from inside your AI agent. This is an MCP server for the ParalonCloud Rental API: it lets Claude Code, Claude Desktop, Cursor, or any MCP client browse GPUs, start a rental, get its connection URL, and stop it — using natural language.

One key for everything: the same prlc_ key powers ParalonCloud's OpenAI-compatible inference API. Build an agent that calls a model and rents the GPU to run the heavy job.

Tools

| Tool | What it does | Cost | | --- | --- | --- | | list_gpus | List rentable GPUs with price, VRAM, compute capability, country | free | | get_balance | Your credit balance | free | | create_rental | Start a Jupyter rental (async → poll) | spends credits | | get_rental | Status + connection URL once running | free | | list_rentals | Your active rentals (status: "all" for history) | free | | destroy_rental | Stop a rental and stop billing | — |

Setup

1. Get a key with the rental scope

1. Create an API key in the Console.
2. Turn on the GPU Rentals scope for that key (rentals are opt-in).
3. Optionally set Max rentals running at once as a safety cap.

Use a dedicated key for the agent, not your production key.

2. Add it to your MCP client

The client passes your key via the PARALON_API_KEY env var — you never edit the server.

Claude Desktop — claude_desktop_config.json:

{
  "mcpServers": {
    "paraloncloud-rentals": {
      "command": "npx",
      "args": ["-y", "@paraloncloud/mcp-rentals"],
      "env": {
        "PARALON_API_KEY": "prlc_your_key_here"
      }
    }
  }
}

Claude Code — one command:

claude mcp add paraloncloud-rentals \
  --env PARALON_API_KEY=prlc_your_key_here \
  -- npx -y @paraloncloud/mcp-rentals

Cursor — .cursor/mcp.json (same shape as Claude Desktop above).

Optional env: PARALON_BASE_URL (defaults to https://paraloncloud.com/api/v1).

3. Try it

"List the cheapest GPUs I can rent, then start a 2-hour Jupyter rental on one with at least 24GB of VRAM."

The agent calls list_gpus, picks a node, and calls create_rental with hours: 2. It then polls get_rental for the Jupyter URL. Say "stop it" and it calls destroy_rental.

Safety

• create_rental and destroy_rental change what you're billed — your MCP client will ask you to approve them (Claude Code/Desktop confirm tool calls by default). Keep that on.
• create_rental auto-generates an idempotency key, so a retried call never starts a second GPU.
• Pass hours so a rental auto-stops even if the agent forgets to.
• The key's max_active_rentals limit (set in the Console) caps concurrency regardless.

Run locally (dev)

PARALON_API_KEY=prlc_your_key_here node server.js

Links

• Rental API docs: https://paraloncloud.com/docs/rental-api
• Console (create keys): https://paraloncloud.com/console
• Inference API: https://paraloncloud.com/docs/inference-api

MIT